Last update: August 30, 2023.

Refereed Journal Papers

  1. Lee, Thomas C. M. (1997), "A Simple Span Selector for Periodogram Smoothing", Biometrika 84, 965-969. [pdf]

  2. Lee, Thomas C. M. and Berman, Mark (1997), "Nonparametric Estimation and Simulation of Two-Dimensional Gaussian Image Textures", Graphical Models and Image Processing 59, 434-445. [pdf]

  3. Hudson, H. Malcolm and Lee, Thomas C. M. (1998), "Maximum Likelihood Restoration and Choice of Smoothing Parameter in Deconvolution of Image Data subject to Poisson Noise", Computational Statistics and Data Analysis 26, 393-410. [pdf]

  4. Lee, Thomas C. M. (1998), "Segmenting Images Corrupted by Correlated Noise", IEEE Transactions on Pattern Analysis and Machine Intelligence 20, 481-492. [pdf]

  5. Lee, Thomas C. M. (1999), "A Stochastic Tessellation for Modelling and Simulating Colour Aluminium Grain Images", Journal of Microscopy 193, 109-126. [pdf]

  6. Lee, Thomas C. M. and Solo, Victor (1999), "Bandwidth Selection for Local Linear Regression: A Simulation Study", Computational Statistics 14, 515-532. [pdf]

  7. Lee, Thomas C. M. (2000), "A Minimum Description Length Based Image Segmentation Procedure, and Its Comparison with a Cross-Validation Based Segmentation Procedure", Journal of the American Statistical Association 95, 259-270. [pdf]

  8. Lee, Thomas C. M. (2000), "Regression Spline Smoothing using the Minimum Description Length Principle", Statistics & Probability Letters 48, 71-82. [pdf]

  9. Talbot, Hugues; Lee, Thomas C. M.; Jeulin, Dominique; Hanton, Daniel and Hobbs, Linn W. (2000), "Image Analysis of Insulation Mineral Fibres", Journal of Microscopy 200, 251-268. [pdf]

  10. Lee, Thomas C. M. (2001), "A Stabilized Bandwidth Selection Method for Kernel Smoothing of the Periodogram", Signal Processing 81, 419-430. [pdf]

  11. Lee, Thomas C. M. (2001), "An Introduction to Coding Theory and the Two-Part Minimum Description Length Principle", International Statistical Review 69, 169-183. [pdf]

  12. Lee, Thomas C. M. (2002), "Automatic Smoothing for Discontinuous Regression Functions", Statistica Sinica 12, 823-842. [paper+support document] [paper only] [support document only].

  13. Lee, Thomas C. M. (2002), "On Algorithms for Ordinary Least Squares Regression Spline Fitting: A Comparative Study", Journal of Statistical Computation and Simulation 72, 647-663. [pdf]

  14. Lee, Thomas C. M. (2002), "Tree-Based Wavelet Regression for Correlated Data using the Minimum Description Length Principle", Australian & New Zealand Journal of Statistics 44, 23-39. [pdf]

  15. Lee, Thomas C. M. (2003), "Smoothing Parameter Selection for Smoothing Splines: A Simulation Study", Computational Statistics and Data Analysis 42, 139-148. [pdf]

  16. Lee, Thomas C. M. and Wong, Tan F. (2003), "Nonparametric Log-Spectrum Estimation using Disconnected Regression Splines and Genetic Algorithms", Signal Processing 83, 79-90. [pdf]

  17. Lee, Thomas C. M. (2004), "Improved Smoothing Spline Regression by Combining Estimates of Different Smoothness", Statistics & Probability Letters 67, 133-140. [pdf]

  18. Hannig, Jan and Lee, Thomas C. M. (2004), "Kernel Smoothing of Periodograms under Kullback-Leibler Discrepancy", Signal Processing 84, 1255-1266. [pdf]

  19. Lee, Thomas C. M. and Oh, Hee-Seok (2004), "Automatic Polynomial Wavelet Regression", Statistics and Computing 14, 337-341. [pdf]

  20. Craiu, Radu V. and Lee, Thomas C. M. (2005), "Model Selection for the Competing Risks Model With and Without Masking", Technometrics 47, 457-467. [pdf]

  21. Oh, Hee-Seok and Lee, Thomas C. M. (2005), "Hybrid Local Polynomial Wavelet Shrinkage: Wavelet Regression with Automatic Boundary Adjustment", Computational Statistics and Data Analysis 48, 809-819. [pdf]

  22. Craiu, Radu V. and Lee, Thomas C. M. (2006), "Pattern Generation using Likelihood Inference for Cellular Automata", IEEE Transactions on Image Processing 15, 1718-1727. [pdf]

  23. Davis, Richard A.; Lee, Thomas C. M. and Rodriguez-Yam, Gabriel A. (2006), "Structural Breaks Estimation for Non-stationary Time Series Models", Journal of the American Statistical Association 101, 223-239. [pdf]

  24. Hannig, Jan and Lee, Thomas C. M. (2006), "On Poisson Signal Estimation under Kullback-Leibler Discrepancy and Squared Risk", Journal of Statistical Planning and Inference 136, 882-908. [pdf]

  25. Hannig, Jan and Lee, Thomas C. M. (2006), "Robust SiZer for Exploration of Regression Structures and Outlier Detection", Journal of Computational and Graphical Statistics 15, 101-117. [pdf]

  26. Huang, Hsin-Cheng and Lee, Thomas C. M. (2006), "Data Adaptive Median Filters for Signal and Image Denoising using a Generalized SURE Criterion", IEEE Signal Processing Letters 13, 561-564. [pdf]

  27. Wang, Haonan and Lee, Thomas C. M. (2006), "Automatic Parameter Selection for a k-Segments Algorithm for Computing Principal Curves", Pattern Recognition Letters 27, 1142-1150. [pdf]

  28. Yao, Fang and Lee, Thomas C. M. (2006), "Penalized Spline Models for Functional Principal Component Analysis", Journal of the Royal Statistical Society Series B 68, 3-25. [pdf]

  29. Lee, Thomas C. M. and Oh, Hee-Seok (2007), "Robust Penalized Regression Spline Fitting with Application to Additive Mixed Modeling", Computational Statistics 22, 159-171.

  30. Oh, Hee-Seok; Nychka, Doug and Lee, Thomas C. M. (2007), "The Role of Pseudo Data for Robust Smoothing with Application to Wavelet Regression", Biometrika 94, 893-904.

  31. Shen, Haipeng; Zhu, Zhengyuan and Lee, Thomas C. M. (2007), "Robust Estimation of Self-similarity Parameter in Network Traffic using Wavelet Transform", Signal Processing 87, 2111-2124.

  32. Whitaker, Stephan and Lee, Thomas C. M. (2007), "An Effective Method for Selecting the Number of Components in Density Mixtures", Journal of Statistical Computation and Simulation 77, 907-914.

  33. Yao, Fang and Lee, Thomas C. M. (2007), "Spectral Density Estimation Using Sharpened Periodograms", IEEE Transactions on Signal Processing 55, 4711-4716.

  34. Davis, Richard A.; Lee, Thomas C. M. and Rodriguez-Yam, Gabriel A. (2008), "Break Detection for a Class of Nonlinear Time Series Models", Journal of Time Series Analysis 29, 834-867.

  35. Gilleland, Eric; Lee, Thomas C. M.; Halley-Gotway, John; Bullock, Randy G. and Brown, Barb (2008), "Computationally Efficient Spatial Forecast Verification using Baddeley's Delta Image Metric", Monthly Weather Review 136, 1747-1757.

  36. Wang, Haonan and Lee, Thomas C. M. (2008), "Extraction of Curvilinear Features from Noisy Point Patterns using Principal Curves", Pattern Recognition Letters 29, 2078-2084.

  37. Whitcher, Brandon; Lee, Thomas C. M.; Weiss, Jeffrey B.; Nychka, Douglas W. and Hoar, Timothy J. (2008), "A Multiresolution Census Algorithm for Calculating Vortex Statistics in Turbulent Flows", Journal of the Royal Statistical Society Series C (Applied Statistics) 57, 293-312.

  38. Yao, Fang and Lee, Thomas C. M. (2008), "An Improved Knot Placement Scheme for Penalized Spline Regression", Journal of the Korean Statistical Society 37, 259-267.

  39. Hannig, Jan and Lee, Thomas C. M. (2009), "Generalized Fiducial Inference for Wavelet Regression", Biometrika 96, 847-860.

  40. Storlie, Curtis B.; Lee, Thomas C. M.; Hannig, Jan and Nychka, Douglas (2009), "Tracking of Multiple Merging and Splitting Targets: A Statistical Perspective (with Commentaries)", Editor Invited Thesis Paper, Statistica Sinica 19, 1-52.

  41. Yao, Fang and Lee, Thomas C. M. (2009), "Automatic and Asymptotically Optimal Data Sharpening for Nonparametric Regression", Journal of Statistical Planning and Inference 139, 4017-4030.

  42. Chan, Ngai-Hang; Lee, Thomas C. M. and Peng, Liang (2010), "On Nonparametric Local Inference for Density Estimation", Computational Statistics and Data Analysis 54, 509-515.

  43. Lai, Randy C. S.; Lee, Thomas C. M.; Wong, Raymond K.W. and Yao, Fang (2010), "Nonparametric Cepstrum Estimation via Optimal Risk Smoothing", IEEE Transactions on Signal Processing 58, 1507-1514.

  44. Lu, QiQi.; Lund, Robert and Lee, Thomas C. M. (2010), "An MDL Approach to the Climate Segmentation Problem", Annals of Applied Statistics 4, 299-319.

  45. Park, Cheolwoo; Lee, Thomas C. M. and Hannig, Jan (2010), "Multiscale Exploratory Analysis of Regression Quantiles using Quantile SiZer", Journal of Computational and Graphical Statistics 19, 497-513.

  46. Wong, Raymond K. W.; Lai, Randy C. S. and Lee, Thomas C. M. (2010), "Structural Break Estimation of Noisy Sinusoidal Signals", Signal Processing 90, 303-312.

  47. Aue, Alexander and Lee, Thomas C. M. (2011), "On Image Segmentation using Information Theoretic Criteria", Annals of Statistics 39, 2912-2935.

  48. Oh, Hee-Seok; Lee, Thomas C. M. and Nychka, Douglas W. (2011), "Fast Nonparametric Quantile Regression with Arbitrary Smoothing Methods", Journal of Computational and Graphical Statistics 20, 510-526.

  49. Storlie, Curtis B.; Hannig, Jan and Lee, Thomas C. M. (2011), "Statistical Consistency of the Data Association Problem in Multiple Target Tracking", Electronic Journal of Statistics 5, 1227-1275.

  50. Yao, Fang; Fu, Yuejiao and Lee, Thomas C. M. (2011), "Functional Mixture Regression", Biostatistics 12, 341-353.

  51. Aue, Alexander; Lee, Thomas C. M. and Wang, Haonan (2012), "Local Bandwidth Selection via Second Derivative Segmentation", Electronic Journal of Statistics 6, 478-500.

  52. Lai, Randy C. S.; Huang, Hsin-Cheng and Lee, Thomas C. M. (2012), "Fixed and Random Effects Selection in Nonparametric Additive Mixed Models", Electronic Journal of Statistics 5, 810-842.

  53. Nosedal-Sancheza, Alvaro; Storlie, Curtis B.; Lee, Thomas C. M. and Christensen, Ronald (2012), "Reproducing Kernel Hilbert Spaces for Penalized Regression: A Tutorial", The American Statistician 66, 50-60.

  54. Hannig, Jan; Lee, Thomas C. M. and Park, Cheolwoo (2013), "Metrics for SiZer Map Comparison", Stat 2, 49-60.

  55. Stenning, David C.; Lee, Thomas C. M.; van Dyk, David A.; Kashyap, Vinay; Sandell, Julia and Young, C. Alex (2013), "Morphological Feature Extraction for Statistical Learning with Applications to Solar Image Data", Statistical Analysis and Data Mining 6, 329-345.

  56. Aue, Alexander; Cheung, Rex C. Y.; Lee, Thomas C. M. and Zhong, Ming (2014), "Segmented Model Selection in Quantile Regression using the Minimum Description Length Principle", Journal of the American Statistical Association 109, 1241-1256.

  57. Han, Shengtong; Wong, Raymond K. W.; Lee, Thomas C. M.; Shen, Linghao; Li, Shuo-Yen R. and Fan, Xiaodan (2014), "A Full Bayesian Approach for Boolean Genetic Network Inference", PLoS ONE 9(12): e115806.

  58. Hannig, Jan; Lai, Randy C. S. and Lee, Thomas C. M. (2014), "Computational Issues of Generalized Fiducial Inference", Computational Statistics and Data Analysis 71, Special Issue on Imprecision in Statistical Data Analysis, 849-858.

  59. Wong, Raymond K. W.; Baines, Paul; Aue, Alexander; Lee, Thomas C. M. and Kashyap, Vinay L. (2014), "Automatic Estimation of Flux Distributions of Astrophysical Source Populations", Annals of Applied Statistics 8, 1690-1712.

  60. Wong, Raymond K. W.; Yao, Fang and Lee, Thomas C. M. (2014), "Robust Estimation for Generalized Additive Models", Journal of Computational and Graphical Statistics 23, 270-289.

  61. Fan, Minjie and Lee, Thomas C. M. (2015), "On Variants of Seeded Region Growing", IET Image Processing 9, 478-485.

  62. Lai, Randy C. S.; Hannig, Jan and Lee, Thomas C. M. (2015), "Generalized Fiducial Inference for Ultrahigh Dimensional Regression", Journal of the American Statistical Association 110, 760-772.

  63. Yau, Chun-Yip; Tang, Chong-Man and Lee, Thomas C. M. (2015), "Estimation of Multiple-Regime Threshold Autoregressive Models with Structural Breaks", Journal of the American Statistical Association, 110, 1175-1186.

  64. Gao, Qi and Lee, Thomas C. M. (2016), "High Dimensional Variable Selection in Regression and Classification with Missing Data", Signal Processing 131, 1-7.

  65. Hannig, Jan; Iyer, Hari; Lai, Randy C. S. and Lee, Thomas C. M. (2016), "Generalized Fiducial Inference: A Review and New Results", Journal of the American Statistical Association 111, 1346-1361.

  66. Huang, Hsin-Cheng and Lee, Thomas C. M. (2016), "High-Dimensional Covariance Estimation under the Presence of Outliers", Statistics and Its Interface 9, Special Issue on Statistical and Computational Theory and Methodology for Big Data, 461-468. (Invited by guest editors.)

  67. Wong, Raymond K. W.; Kashyap, Vinay L.; Lee, Thomas C. M. and van Dyk, David A. (2016), "Detecting Abrupt Changes in the Spectra of High-Energy Astrophysical Sources", Annals of Applied Statistics 10, 1107-1134.

  68. Wong, Raymond K. W.; Lee, Thomas C. M.; Paul, Debashis and Peng, Jie (2016), "Fiber Direction Estimation, Smoothing and Tracking in Diffusion MRI (with Discussions)", Annals of Applied Statistics 10, 1137-1169.

  69. Aue, Alexander; Cheung, Rex C. Y.; Lee, Thomas C. M. and Zhong, Ming (2017), "Piecewise Quantile Autoregressive Modeling For Non-stationary Time Series", Bernoulli 23, 1-22.

  70. Cheung, Rex C. Y.; Aue, Alexander and Lee, Thomas C. M. (2017), "Consistent Estimation for Partition-wise Regression and Classification Models", IEEE Transactions on Signal Processing 65, 3662-3674.

  71. Gao, Qi; Lee, Thomas C. M.; Yau, Chun Yip (2017), "Nonparametric Modeling and Break Point Detection for Time Series Signal of Counts", Signal Processing 138, 307-312.

  72. McConville, Kelly S.; Breidt, F. Jay; Lee, Thomas C. M. and Moisen, Gretchen G. (2017), "Model-Assisted Survey Regression Estimation with the Lasso", Journal of Survey Statistics and Methodology 5, 131-158.

  73. Wong, Raymond K. W. and Lee, Thomas C. M. (2017), "Matrix Completion with Noisy Entries and Outliers", Journal of Machine Learning Research 18, 1-25.

  74. Wong, Raymond K. W.; Storlie, Curtis B. and Lee, Thomas C. M. (2017), "A Frequentist Approach to Computer Model Calibration", Journal of the Royal Statistical Society Series B 79, 635-648.

  75. Fan, Minjie; Paul, Debashis; Lee, Thomas C. M. and Matsuo, Tomoko (2018), "A Multi-Resolution Model for Non-Gaussian Random Fields on a Sphere with Application to Ionospheric Electrostatic Potentials", Annals of Applied Statistics 12, 459-489.

  76. Fan, Minjie; Paul, Debashis; Lee, Thomas C. M. and Matsuo, Tomoko (2018), "Modeling Tangential Vector Fields on a Sphere", Journal of the American Statistical Association 113, 1625-1636.

  77. Wang, Justin; Wong, Raymond K. W. and Lee, Thomas C. M. (2019), "Locally Linear Embedding with Additive Noise", Pattern Recognition Letters 123, 47-52.

  78. Cheung, Rex C. Y.; Aue, Alexander; Hwang, Seungyong and Lee, Thomas C. M. (2020), "Simultaneous detection of multiple change points and community structures in time series of networks", IEEE Transactions on Signal and Information Processing over Networks 6, 580-591.

  79. Gao, Qi; Lai, Randy C. S.; Lee, Thomas C. M. and Li, Yao (2020), "Uncertainty Quantification for High Dimensional Sparse Nonparametric Additive Models", Technometrics 62, 513-524.

  80. Lopes, Miles E.; Wu, Suofei and Lee, Thomas C. M. (2020), "Measuring the Algorithmic Convergence of Randomized Ensembles: The Regression Setting", SIAM Journal on Mathematics of Data Science 2, 921-943.

  81. Su, Yi; Wong, Raymond K. W. and Lee, Thomas C. M. (2020), "Network Estimation via Graphon with Node Features", IEEE Transactions on Network Science and Engineering 7, 2078-2089.

  82. Lai, Randy C. S.; Hannig, Jan and Lee, Thomas C. M. (2021), "Method G: Uncertainty Quantification for Distributed Data Problems using Generalized Fiducial Inference", Journal of Computational and Graphical Statistics 30, 934-945.

  83. Matsuo, Tomoko; Fan, Minjie; Shi, Xueling; Miller, Caleb; Ruohoniemi, J. Michael; Paul, Debashis and Lee, Thomas C. M. (2021), "Multiresolution Modeling of High-latitude Ionospheric Electric Field Variability and Impact on Joule Heating Using SuperDARN Data", Journal of Geophysical Research - Space Physics 126, e2021JA029196.

  84. Shi, W. Jenny; Hannig, Jan; Lai, Randy C. S. and Lee, Thomas C. M. (2021), "Covariance Estimation via Fiducial Inference", Statistical Theory and Related Fields 5, 316-331.

  85. Wu, Suofei; Hannig, Jan and Lee, Thomas C. M. (2021), "Uncertainty Quantification for Principal Component Regression", Electronic Journal of Statistics 15, 2157-2178.

  86. Xu, Cong; Gunther, Hans Moritz; Kashyap, Vinay; Lee, Thomas C. M. and Zezas, Andreas (2021), "Change Point Detection and Image Segmentation for Time Series of Astrophysical Images", Astronomical Journal 161, 184.

  87. Han, Yi and Lee, Thomas C. M. (2022), "Uncertainty Quantification for Sparse Estimation of Spectral Lines", IEEE Transactions on Signal Processing 70, 6243- 6256.

  88. Hwang, Seungyong; Lai, Randy C. S. and Lee, Thomas C. M. (2022), "Generalized Fiducial Inference for Threshold Estimation in Dose-Response and Regression Settings", Journal of Agricultural, Biological and Environmental Statistics 27, 109-124.

  89. Li, Yao; Cheng, Minhao; Hsieh, Cho-Jui and Lee, Thomas C. M. (2022), "A Review of Adversarial Attack and Defense for Classification Methods", The American Statistician 76, 329-345.

  90. Su, Yi; Hannig, Jan and Lee, Thomas C. M. (2022) "Uncertainty Quantification in Graphon Estimation using Generalized Fiducial Inference", IEEE Transactions on Signal and Information Processing over Networks 8, 597-609.

  91. Wang, Justin; Lee, Marie A. and Lee, Thomas C. M. (2022), "When might We Break the Rules? A Statistical Analysis of Aesthetics in Photographs", PLOS One 17, e0269152.

  92. Wu, Suofei; Hannig, Jan and Lee, Thomas C. M. (2022), "Uncertainty Quantification for Ensembles of Honest Regression Trees", Computational Statistics and Data Analysis 167, 107377.

  93. Xu, Cong and Lee, Thomas C. M. (2022), "Change Point Detection and Node Clustering for Time Series of Graphs", IEEE Transactions on Signal Processing 70, 3165-3180.

  94. Xu, Cong and Lee, Thomas C. M. (2022), "Statistical Consistency for Change Point Detection and Community Estimation in Time-Evolving Dynamic Networks", IEEE Transactions on Signal and Information Processing over Networks 8, 215-227.

  95. Zhang, Chunzhe; Storlie, Curtis B. and Lee, Thomas C. M. (2022), "Sensitivity Analysis in Classification using Bayesian Smoothing Spline ANOVA Probit Regression", Canadian Journal of Statistics 50, 928-950.

  96. Fan, Minjie; Wang, Jue; Kashyap, Vinay L.; Lee, Thomas C. M.; van Dyk, David A. and Zezas, Andreas (2023), "Identifying Diffuse Spatial Structures in High-energy Photon Lists", The Astronomical Journal 165, 66.

  97. Wei, Zhenyu and Lee, Thomas C. M. (2023), "High-Dimensional Multi-Task Learning using Multivariate Regression and Generalized Fiducial Inference", Journal of Computational and Graphical Statistics 32, 226-240.